Products

The "Python 2 with Ubuntu 20.04 LTS" offering provides a pre-configured Amazon Machine Image (AMI) that combines Python 2.7 with Ubuntu 20.04 LTS. This setup is tailored for developers and organizations that require Python 2.7 for legacy applications while benefiting from the stability and security features of Ubuntu 20.04 LTS. By deploying this AMI on AWS, users can efficiently run and maintain their Python 2-based applications in a cloud environment. Key Features and Functionality: - Pre-Con

The "Python 2.7 on Ubuntu 20.04 LTS" Amazon Machine Image (AMI) offers a pre-configured environment combining Python 2.7 with Ubuntu 20.04 LTS. This setup is tailored for users who require Python 2.7 for legacy applications while benefiting from the stability and features of Ubuntu 20.04 LTS. Key Features and Functionality: - Pre-Installed Python 2.7: Provides immediate access to Python 2.7, eliminating the need for manual installation. - Ubuntu 20.04 LTS Base: Leverages the long-term support

The "Python 2 with CentOS 8.2" offering provides a pre-configured Amazon Machine Image (AMI) that combines CentOS 8.2, a robust and secure Linux distribution, with Python 2.7, a widely-used programming language. This AMI is designed to facilitate the deployment of applications that depend on Python 2.7, ensuring compatibility and stability for legacy systems. Key Features and Functionality: - Pre-Installed Python 2.7: The AMI comes with Python 2.7 pre-installed, allowing immediate development

Theano, a numerical computation library for Python, and Python, a high-level programming language for general-purpose programming

The "Caffe Python 3.6 CPU Production on Ubuntu" is an Amazon Machine Image (AMI) designed to provide a ready-to-use environment for deploying and running deep learning applications using the Caffe framework on Ubuntu. This AMI is tailored for CPU-based computations, making it suitable for users who prefer or require CPU processing over GPU acceleration. Key Features and Functionality: - Preconfigured Environment: The AMI comes with Caffe and Python 3.6 fully installed and configured, allowing

Python 2.7 with Ubuntu 18.04 LTS, offered by Cognosys Inc., is a pre-configured Amazon Machine Image (AMI) designed to facilitate seamless development and deployment of applications. This solution combines the versatility of Python 2.7 with the stability of Ubuntu 18.04 LTS, providing developers with a robust environment for building and running various software applications. Key Features and Functionality: - Pre-Configured Environment: The AMI comes with Python 2.7 and Ubuntu 18.04 LTS pre-in

The MXNet 1 Python 3.6 CPU Production environment is a pre-configured software stack that integrates Apache MXNet, an open-source deep learning framework, with Python 3.6. This setup offers a stable and tested execution environment optimized for CPU-based tasks, facilitating efficient training, inference, and deployment of deep learning models. It is designed to seamlessly integrate into continuous integration and deployment workflows, making it suitable for both short and long-running high-perf

The MySQL and MariaDB Python Connector by Devart is a robust and user-friendly solution designed to facilitate seamless interaction between Python applications and MySQL or MariaDB database servers. Fully implementing the Python DB API 2.0 specification, this connector enables developers to perform create, read, update, and delete operations efficiently. Distributed as a wheel package, it supports multiple platforms, including Windows, macOS, and Linux. Key Features and Functionality: - Direct

The PyTorch 0.3 Python 2.7 CPU Notebook is a pre-configured and fully integrated runtime environment designed for machine learning and data science applications. It combines PyTorch 0.3, an open-source machine learning library, with Python 2.7 and Jupyter Notebook, a browser-based interactive platform for programming and data analysis. This stack is optimized for CPU performance, providing a stable and tested execution environment suitable for both short and long-running high-performance tasks.

The "Python 3 Minimal with Ubuntu 18.04 LTS" Amazon Machine Image (AMI) offers a streamlined and efficient environment for developers seeking to deploy Python-based applications on AWS. This AMI combines the versatility of Python 3 with the stability of Ubuntu 18.04 LTS, providing a reliable foundation for various development projects. Key Features and Functionality: - Pre-installed Python 3: Ensures immediate readiness for Python development without additional setup. - Minimal Ubuntu 18.04 L

This product has charges associated with it, which includes AWS support. Debian 10 "buster" Server is suitable for many different use cases. Secure, Scalable & Faster.

The AISE TensorFlow 1.8 Python 2.7 CPU Notebook is a pre-configured, fully integrated runtime environment designed for machine learning and data science applications. It combines TensorFlow 1.8, an open-source machine learning library; Keras 2.1.6, a neural network library; Jupyter Notebook 1.0.0, an interactive web-based notebook; and Python 2.7.14. This stack is optimized for CPU performance using Intel's Math Kernel Library and MKL-DNN, ensuring efficient execution of machine learning tasks.

The AISE TensorFlow 1.8 Python 3.6 CUDA 9.1 Notebook is a pre-configured, fully integrated runtime environment designed for machine learning and deep learning applications. It combines TensorFlow 1.8, Keras, Python 3.6, and Jupyter Notebook, all optimized for NVIDIA GPU acceleration using CUDA 9.1 and cuDNN. This setup provides data scientists and developers with a ready-to-use platform, eliminating the complexities of manual installation and configuration. Key Features and Functionality: - Te

The AISE PyTorch 0.4 Python 2.7 CPU Notebook is a pre-configured and fully integrated software stack designed for machine learning and data science applications. It combines PyTorch 0.4, an open-source machine learning library, with Python 2.7 and Jupyter Notebook, a browser-based interactive environment for programming and data analysis. This setup is optimized for CPU performance, providing a stable and production-ready environment for both short and long-running high-performance tasks. Key F

MXNet, an open-source deep learning framework, and Python, a high-level programming language for general-purpose programming

The AISE PyTorch 0.4.1 Python 2.7 CUDA 9.2 Notebook is a pre-configured Amazon Machine Image (AMI) designed to facilitate deep learning development on AWS. It integrates PyTorch 0.4.1, Python 2.7, and CUDA 9.2, providing a ready-to-use environment for machine learning practitioners. This setup enables users to leverage GPU acceleration for training and deploying deep learning models efficiently. Key Features and Functionality: - Pre-Configured Environment: Combines PyTorch 0.4.1, Python 2.7, a

AISE TensorFlow 1.10 Python 2.7 CPU MKL Production is a pre-configured Amazon Machine Image (AMI) designed to provide a robust and efficient environment for developing and deploying machine learning models. This AMI integrates TensorFlow 1.10, Python 2.7, and Intel's Math Kernel Library (MKL to optimize performance on CPU-based instances. It offers a stable and production-ready setup, enabling users to focus on building and training models without the overhead of manual configuration. Key Featu

AISE PyTorch 0.4.1 Python 2.7 CUDA 9.2 Production is a pre-configured and fully integrated software stack designed for machine learning applications. It combines PyTorch 0.4.1, Python 2.7, and CUDA 9.2, providing a stable and optimized environment for developing and deploying deep learning models. This stack is tailored for high-performance tasks, ensuring compatibility and efficiency in both training and inference processes. Key Features and Functionality: - Pre-configured Environment: The st

The AISE TensorFlow 1.7 Python 3.6 CPU Notebook is a pre-configured, fully integrated runtime environment designed for machine learning and data science applications. It combines TensorFlow 1.7, an open-source machine learning library, with Python 3.6 and Jupyter Notebook, a browser-based interactive platform for programming and data analysis. This setup is optimized for CPU performance, providing a stable and efficient environment for developing and deploying machine learning models. Key Featu

The AISE PyTorch 0.4 Python 3.6 CPU Notebook is a pre-configured, fully integrated runtime environment designed for machine learning and data science applications. It combines PyTorch 0.4, an open-source machine learning library, with Python 3.6 and Jupyter Notebook, a browser-based interactive platform for programming and data analysis. Optimized for CPU performance, this environment facilitates efficient development and execution of machine learning models without the need for GPU resources.